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Titlebook: Computational Vaccine Design; Pedro A. Reche Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springe

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楼主: hearken
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https://doi.org/10.1007/978-3-642-50786-1his chapter, we describe the use of TAPREG, a tool for predicting TAP binding affinity that has been enhanced to identify potential CD8 T cell epitope precursors transported by TAP. TAPREG is available for free public use at ..
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Unbiased, High-Throughput Identification of T Cell Epitopes by ELISPOTting of all peptides that constitute the potential epitope space in that person. The goal of comprehensive, high-throughput epitope mapping can be readily established by the methods described in this chapter.
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https://doi.org/10.1007/978-3-662-49476-9ical states. This protocol has three parts: (1) data preprocessing, (2) labeling of reference PBMC SCT datasets and training supervised ML models, and (3) labeling new PBMC datasets from disease samples. This protocol enables building classification models that are of high accuracy and efficiency. O
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https://doi.org/10.1007/978-3-662-49476-9yer interferometry (BLI)-based methods to evaluate such epitopes and permit simultaneous analysis of antibodies from several sources, including monoclonal antibodies (mAbs) and polyclonal serum antibodies (pAbs). Using previously characterized antibodies with known epitopes as controls, the distribu
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https://doi.org/10.1007/978-3-662-49476-9e immune system, infectious diseases, cancer, and vaccine development. Single-cell transcriptomics (SCT) allows the labeling of cell types by gene expression patterns from biological samples. Classifying cells into cell types and states is essential for single-cell analyses, especially in the classi
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